adlfs
Access Azure Blobs and Data Lake Storage (ADLS) Gen2 with fsspec and dask
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained with no known vulnerabilities, low install friction, and a permissive BSD license. It solves a real problem—fsspec-compatible access to Azure storage—and integrates cleanly with the Azure Python SDK ecosystem. Install if you need to read from or write to Azure Blob Storage or Data Lake Storage Gen2 through fsspec.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.10.
- Azure credentials (account name/key, connection string, or service principal) must be provided or discoverable via DefaultAzureCredential.
- Low friction install with a pure-Python wheel.
License · maintenance · safety
BSD (permissive) — BSD license is permissive; you can use, modify, and distribute this package with minimal restrictions, suitable for both open-source and commercial projects.
last release 2026-08-11 (3 days) · last repo commit 2026-08-11 · 210 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 15,918,404 downloads/mo, #1,170 on PyPI
Alternatives
Verify before relying
pip install adlfs
import fsspec
storage_options = {'account_name': 'myaccount', 'account_key': 'mykey'}
fs = fsspec.filesystem('abfs', **storage_options)
files = fs.ls('container/folder')- Performance characteristics when reading or writing large files or many small files to Azure storage.
- Whether append operations on AppendBlobs work reliably with hierarchical namespaces disabled.
- Compatibility with Dask beyond the documented read_csv and read_parquet examples.
What it is and what it does
adlfs implements filesystem-like access to Azure Blob Storage and Azure Data Lake Storage Gen2 through fsspec, allowing you to interact with cloud storage using familiar file operations (read, write, list) via the `abfs://` and `az://` protocols. The package wraps the official Azure Blob Storage Python SDK and registers itself in fsspec's known_implementations, so tools that support fsspec can transparently access Azure storage.
Authentication is flexible: the package can use DefaultAzureCredential for automatic discovery, or accept explicit credentials via account keys, connection strings, SAS tokens, or service principals passed through storage_options. Write operations create BlockBlobs by default; AppendBlobs are available via `mode="ab"`. The package supports multiple URI formats and can read from public containers when provided with an account name.
Use it for
- Read CSV or Parquet files from Azure storage using fsspec-compatible tools without downloading to local disk.
- Access public Azure datasets by specifying the account name and using anonymous credentials.
- Integrate Azure Blob Storage into ETL pipelines that use fsspec, treating cloud storage as a mounted filesystem.
- Write processed data back to Azure storage without staging to local disk.
- Authenticate to Azure storage using service principals or managed identities in automated environments.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained with no known vulnerabilities, low install friction, and a permissive BSD license. It solves a real problem—fsspec-compatible access to Azure storage—and integrates cleanly with the Azure Python SDK ecosystem. Install if you need to read from or write to Azure Blob Storage or Data Lake Storage Gen2 through fsspec.
Install
adlfs on PyPI
Before you install
Low friction install with a pure-Python wheel. Actively maintained with a recent release 3 days old. Depends on four Azure SDK packages and fsspec, all stable and widely used.
Requires Python >=3.10. Azure credentials (account name/key, connection string, or service principal) must be provided or discoverable via DefaultAzureCredential.
License in practice
BSD license is permissive; you can use, modify, and distribute this package with minimal restrictions, suitable for both open-source and commercial projects.
Quickstart
pip install adlfs
import fsspec
storage_options = {'account_name': 'myaccount', 'account_key': 'mykey'}
fs = fsspec.filesystem('abfs', **storage_options)
files = fs.ls('container/folder')Verify before relying
- Performance characteristics when reading or writing large files or many small files to Azure storage.
- Whether append operations on AppendBlobs work reliably with hierarchical namespaces disabled.
- Compatibility with Dask beyond the documented read_csv and read_parquet examples.
Package facts
| License | BSD permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesazure-coreazure-identityazure-storage-blobfsspec |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 15,918,404 / month, #1,170 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: BSD LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: adlfs-2026.8.0-py3-none-any.whl
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See also azure-datalake-store · azure-storage-file-datalake · msgraphfs · pyarrowfs-adlgen2 · ocifs · azureml-fsspec · dvc-azure · webdav4 · fsspec · python-dxf